{"id":"W3004403696","doi":"10.48550/arxiv.2001.10657","title":"The Indian Chefs Process","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Nonparametric statistics; Prior probability; Directed acyclic graph; Bayesian network; Computer science; Joint probability distribution; Artificial intelligence; Bayesian probability; Mathematics; Machine learning; Algorithm; Econometrics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003822504,0.000852217,0.001478659,0.002414743,0.00126489,0.003119353,0.00250522,0.002457457,0.01375444],"category_scores_gemma":[0.01908334,0.0009163919,0.001606591,0.001937924,0.005141399,0.006391729,0.002633002,0.00514126,0.002203036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002079623,"about_ca_system_score_gemma":0.001920168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007058015,"about_ca_topic_score_gemma":0.005155104,"domain_scores_codex":[0.9980726,0.0007561476,0.00005662168,0.0004598506,0.0003879024,0.0002667859],"domain_scores_gemma":[0.9936932,0.003750468,0.0005157653,0.0009305705,0.0006933742,0.0004167107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002727833,0.00001242531,0.0004724805,0.00001959866,0.00001320298,0.00004526317,0.0001005912,0.02571006,0.0001814624,0.9648872,0.001809414,0.006720886],"study_design_scores_gemma":[0.00001375592,0.00001349916,0.000267134,0.00004503622,0.00001165306,0.00005671132,0.00003781682,0.2451517,0.0002155174,0.7490867,0.005071895,0.00002860045],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02432024,0.0006889949,0.9504436,0.001969934,0.0001912598,0.00006243738,0.0006080404,0.0004349325,0.02128055],"genre_scores_gemma":[0.7867272,0.002486615,0.1614975,0.001668301,0.0006640881,0.0004663517,0.001108211,0.0005963166,0.04478548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01375444,"threshold_uncertainty_score":0.04601312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07867511522997653,"score_gpt":0.2088669814503986,"score_spread":0.1301918662204221,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}